A Choquet integral-based approach to multiattribute decision-making with correlated periods
Tipo de publicación: International Journal
Año de publicación: 2018
Autores: Yeleny Zulueta
Director: Lina García-Cabrera
Tipo: Granular Computing
Editorial: Springer
Fecha de publicación: 09/2018
Volumen: 3
Número: 3
Paginación: 245-256
Numero ISSN: 2364-4974
Resumen: "Dynamic multiattribute decision-making (DMADM) problems are very common in real life and meaningful as research topic. In this paper, the focus is the DMADM problems with correlated periods, in which the attribute assessment values take the form of 2-tuple linguistic values. The concept of the discrete time 2-tuple linguistic variable where is introduced to describe a collection of 2-tuple linguistic values collected from different periods. To aggregate 2-tuple information gathered in multiple periods whose importance are interdependent or interactive, the 2-tuple linguistic dynamic correlated averaging \$\$2\backslashmathrm\TDCA\\_\\backslashvartheta \\$\$2TDCAϑand the 2-tuple linguistic dynamic correlated geometric \$\$2\backslashmathrm\TDCG\\_\\backslashvartheta \\$\$2TDCGϑaggregation operators are developed based on the Choquet integral. A 2-tuple linguistic DMADM approach based on \$\$2\backslashmathrm\TDCA\\_\\backslashvartheta \\$\$2TDCAϑand \$\$2\backslashmathrm\TDCG\\_\\backslashvartheta \\$\$2TDCGϑaggregation operators is also presented. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicability and effectiveness."
URL: https://doi.org/10.1007/s41066-018-0095-4
DOI: 10.1007/s41066-018-0095-4